面向精密调整的6-HTRT并联机器人

为实现光学精密调整,研制出了由交流伺服电机驱动的6-HTRT并联机器人,它具有6个自由度,其结构特点决定了该机器人可以完成高精度定位调整。分析了机器人的位置逆解,并对不同位姿下的工作空间进行了仿真。控制系统采用基于ISA总线的闭环控制方式,测试结果显示:该并联机器人工作空间较大、分辨率高、重复定位精度高,说明机器人结构和控制系统设计的合理性。最后应用此并联机器人成功完成了光学精密装配试验。     

循环神经网络前馈补偿的压电驱动器跟踪控制

压电驱动器固有的迟滞特性,以及其他动态特性严重地影响其跟踪性能.循环神经网络能够准确拟合非线性系统,并且具有记忆存储能力,本文设计了一种循环神经网络对压电驱动器的迟滞特性进行建模,进而得到能够准确模拟输出位移和输入电压之间关系的逆模型,并据此对压电驱动器进行前馈补偿.此外,考虑到建模误差以及其他扰动对驱动器跟踪精度的影...     

Neural network position control of XY piezo actuator stage by visual feedback

This paper describes the visual feedback positional control of the XY piezo actuator stage (PAS). The XY PAS control system consists of four main components, i.e. XY PAS as controlled object, supply electronics for piezoelectric actuators (PEAs), microscope with digital camera for visualization and for measuring the actual position and a vision processing module in combination with a desktop PC, as processing hardware. XY PAS is fabricated by a photo structuring process from photosensitive glass, and PEAs are built-onto meet the request for its precise movement. It is evident from the electromechanical model of XY PAS, that accurate positioning of XY PAS is an exacting piece of work, due to the nonlinear hysteresis inherent in PEAs. Accordingly, two neural network control techniques were developed, i.e. the feedforward neural network controller (FFNNC) and the feedforward/feedback neural network controller (FF/FBNNC). Proposed neural network controllers are compared with the traditional linear controllers.     

System identification of a novel 6-DOF precision positioning table

The purpose of this study is to identify a novel 6-DOF precision positioning table, which is assembled by two different 3-DOF precision positioning tables: a plane-type 3-DOF (X, Y, θ_z) precision positioning table and a cylinder-type 3-DOF (θ_x, θ_y, Z) one. According to the dynamics of a mechanical mass-spring system, we establish simple mathematical equations that contain linear mass (inertia), viscous friction, and spring stiffness associated with cross-coupling effects due to mechanical bending. In system identification, we identify parameters of this 6-DOF and two 3-DOF precision positioning tables driven by piezoelectric actuators with hysteresis phenomenon, which is described by Bouc–Wen model. The identification method based on the real-coded genetic algorithm (RGA) has the advantages to identify all the parameters of the table and the hysteresis model simultaneously. From experimental results and numerical simulations, it is found that the numerically identified parameters are almost the same as those of the real system. In comparison of the identified results between the integral and individual tables, it is found that the integral table has better performance than those from the individual table.     

A fast non-singular terminal sliding mode control based on perturbation estimation for piezoelectric actuators systems

Piezoelectric actuators (PEAs) are the key devices in micro/nano positioning system. However, the PEA performance is significantly degraded by the inherent non-linear behaviour. This behaviour is a consequence of the hysteresis properties contained within PEAs. Therefore, in micro/nano positioning applications, a robust control system has to be adopted for such actuators. This paper proposes a systematic control method that utilises a fast non-singular terminal sliding mode (FNTSM) based on online perturbation estimation technique for PEAs. Unlike other sliding mode methods, the FNTSM control method is characterised by chatter free. Besides, a zero error convergence can be guaranteed in finite time in the presence of disturbance and system uncertainties (i.e., hysteresis and gain changes). The design of the FNTSM control based on perturbation estimation (FNTSMPE) is presented. A model-free robust exact differentiator is used to estimate the states of the feedback system from merely measurable position signal. Theoretical analysis and the experimental results of FNTSMPE control reveal that high-precision and robust performance is achieved in comparison with ordinary FNTSM control.     

基于反步法的欠驱动UUV的3维路径跟踪控制

研究了欠驱动无人水下航行器(unmanned underwater vehicle,UUV)在3维空间中的路径跟踪控制器设计及其稳定性分析问题.首先建立2阶积分器形式的欠驱动UUV空间6自由度运动模型和动力学模型.针对该运动模型,以位置误差作为虚拟控制变量,基于反步法(backstepping)设计路径跟踪控制器.根据李亚普诺夫理论,在理论上证明了所设计的路径跟踪控制系统是稳定的.该控制器实现了欠驱动UUV 3维空间的路径跟踪控制.仿真结果验证了控制器的有效性.     

A hysteresis compensation method of piezoelectric actuator: Model,identification and control

A major deficiency of piezoelectric actuators is that their open-loop control accuracy is seriously limited by hysteresis. In this paper, a novel mathematical model is proposed to describe hysteresis precisely. Based on the hysteresis model, an adaptive inverse control approach is presented for reducing hysteresis. The weights of the main hysteresis loop are identified by using least mean square (LMS) algorithm. The realization of an inverse feedforward controller for the linearization of a piezoelectric actuator is formulated. Experiments were performed on a micro-positioning system driven by piezoelectric actuators. The experimental results demonstrate that the positioning precision is noticeably improved in open-loop operation compared to the conventional open-loop control without any compensation.     

航天器姿轨耦合非线性同步控制

研究航天器飞行稳定控制建模问题。航天器动力学模型的精确建立,要求采用单独建立轨道或姿态的模型无法满足任务高精度要求,从非线性相对轨道动力学方程和修正罗德里格斯参数(MRP)表示的姿态运动学方程出发,建立了航天器六自由度的相对耦合动力学方程。为了给出姿轨运动的基准,分别设计了航天器理想姿态和椭圆加指数接近轨道。针对耦合非线性动力学方程设计了非线性同步控制律,并通过Lyapunov证明闭环系统的全局渐近稳定性。通过仿真结果可以看出,非线性同步控制算法能使轨道和姿态误差逐步趋于零,为航天器姿轨耦合设计提供了依据。     

TriM: An Ultra-Accurate High-Speed Six Degree-of-Freedom Manipulator Using Planar Stepper Motors

In this paper, we propose a novel six degree-of-freedom positioning system. This mechanism is a tripod structure with inextensible limbs actuated at the base by two-dimensional linear stepper motors (other types of actuators may also be utilized). This manipulator has a closed-chain kinematic structure. Both the direct and the inverse kinematics of the manipulator are presented in detail. While the inverse kinematics are obtained in closed form, the direct kinematics can not be solved in closed form and an algorithm is provided for numerically computing the direct kinematic solution. A detailed dynamic model of the positioning system is also provided. The dynamics of the actuators (Sawyer motors) are also included in the dynamic modeling. The design of the tripod manipulator (TriM) included a kinematic optimization of the system parameters to maximize the manipulator workspace. The proposed manipulator achieves large range of motion in all the 6 degrees of freedom. Furthermore, high resolution and high speed motion may be achieved in all axes due to the actuators used and the direct-drive nature of the manipulator. This work was supported in part by NSF under grants ECS-9977693 and ECS-0501539. An earlier version of this paper was presented at the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, Oct. 2003.     

Hysteresis Compensation and Adaptive Controller Design for a Piezoceramic Actuator System in Atomic Force Microscopy

This paper presents an indirect adaptive controller combined with hysteresis compensation to achieve high accuracy positioning control of piezoceramic actuators and illustrates the results with an atomic force microscope (AFM) application. A dynamic model of a piezoceramic actuator system in AFM is derived and analyzed. A feedforward controller based on the Preisach model is proposed to compensate for the nonlinear hysteresis effects. Then an indirect adaptive controller is designed to achieve desired tracking performance as well as deal with the uncompensated nonlinearity from hysteresis and the system parameter variation due to creep. Experimental results indicate that the proposed controller can significantly improve the positioning control accuracy of the piezoceramic actuator as well as achieve high image quality of the AFM system. The maximum scanning error was reduced from 2µm to 0.3µm in comparison with a proportional‐integral‐derivative (PID) controller. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Modeling and configuration-independent control of a self-mobile space manipulator

TheSelf-Mobile Space Manipulator (SM ²) is a 5-DOF, 1/3-scale, laboratory version of a robot designed to walk on the trusswork and other exterior surfaces of Space Station Freedom. It will be capable of routine tasks such as inspection, parts transportation and simple maintenance and repair. We have designed and built the robot and gravity compensation system to permit simulated zero-gravity experiments. The control ofSM ² is challenging because of significant structural flexibility, relatively high friction at the joints, positioning error amplified from joint errors due to the long reach, and high performance requirements for general 3-D locomotion. In this paper, we focus on the modeling of the robot system and the design of the control system based on the model. We address the kinematics and dynamic modeling of the 3-D motion ofSM ² and demonstrate the simulation and experimental modal analysis results. The robot dynamic characteristics vary significantly when the robot configuration changes. To consider this effect, we develop a control system that is composed of two basic parts, the model-based part and the servo part. The model-based loop can be updated based on the off-line dynamic model, and the servo control loop is updated by a gain schedule according to the off-line relationship between the closed-loop frequency and the modal frequency estimated from the off-line dynamic model. By taking dynamic variation into account in the controller, the control system is independent of the robot configuration, and the motion performance ofSM ² is greatly enhanced in implementation.     

Tracking of piezoelectric actuators with hysteresis: A nonlinear robust output regulation approach

Hysteretic characteristics commonly exist in piezoelectric actuators (PEAs) and degrade the positioning accuracy particularly in the case of low‐frequency trajectory tracking. A PEA with hysteretic characteristics is usually difficult to precisely control because the unmeasurable hysteretic force is typically generated by a complicated nonlinear dynamic model. This task can be theoretically formulated as a robust output regulation problem with a specific nonlinear and non‐autonomous exosystem. In this paper, the theoretical problem is first solved within a novel internal model architecture. With the proposed controller, the PEA is able to asymptotically track a desired reference trajectory with the robustness to plant uncertainties. The effectiveness of the design is verified by extensive experiments. Copyright © 2016 John Wiley & Sons, Ltd.     

Decoupling and control of micromotion stage based on hysteresis of piezoelectric actuation

This paper presents the mechanism and control design of a micro-motion stage, which employs the right-angle flexure hinges and piezoelectric actuators (PZT). Aiming at the mechanism with the characteristics of a large stroke and three degrees of freedom, analytical models of statics and dynamics are established; especially the coupling motions of stage are investigated, which are verified by finite element analysis simulation. Via open-loop experiment, the decoupling property is well certified. Owing to the hysteresis of PZT, the dynamic equation of system with Bouc–Wen hysteresis model is proposed, which is identified through the Least squares. Moreover, a closed-loop controller of proportion integral derivative combined with the inverse hysteresis model-based feedforward is developed to reduce the nonlinearity and uncertainty, which can improve the positioning accuracy. Besides, the single-axis and multi-axis motions are tested. Experimental results reveal that the stage has a well-decoupling performance, and the effectiveness of proposed Bouc–Wen model is validated under open-loop control. Furthermore, the micro-motion performance in single- and multi-axis motions can be achieved as well.

     

基于Paden-kahan子问题的冗余度机器人运动学求解

针对7DOF机器人的逆运动学求解问题,提出了一种可提高运动控制精度的混合算法.这种算法使用 旋量理论来描述机器人的运动.它首先求出对运动学性能指标进行优化的速度级逆解;然后固定一个特殊关节,将 问题转化为非冗余度机器人的运动控制,应用Paden-Kahan子问题法得到逆运动学封闭解.通过仿真实例,证实了 这种混合算法的有效性.     

利用GPS进行车辆动态定位的自适应模型研究

提出一种GPS动态定位系统模型,并将其应用于车辆的导航定位系统,获得了明显效果.将GPS的误差等效为马尔柯夫过程,采用描述机动载体运动的"当前"统计模型,建立了一种利用GPS对车辆进行动态导航定位的滤波模型及自适应卡尔曼滤波算法.仿真结果表明,应用所提出的强跟踪动态定位模型和算法,与改进前相比车辆导航定位系统的精度、实用性均得到了明显提高.     

Dynamic modeling and redundant force optimization of a 2-DOF parallel kinematic machine with kinematic redundancy

High precision is still one of the challenges when parallel kinematic machines are applied to advanced equipment. In this paper, a novel planar 2-DOF parallel kinematic machine with kinematic redundancy is proposed and a method for redundant force optimization is presented to improve the precision of the machine. The inverse kinematics is derived, and the dynamic model is modeled with the Newton–Euler method. The deformations of the kinematic chains are calculated and their relationship with kinematic error of the machine is established. Then the size and direction of the redundant force acting on the platform are optimized to minimize the position error of the machine. The dynamic performance of the kinematically redundant machine is simulated and compared with its two corresponding counterparts, one is redundantly actuated and the other is non-redundant. The proposed kinematically redundant machine possesses the highest position precision during the motion process and is applied to develop a precision planar mobile platform as an application example. The method is general and suitable for the dynamic modeling and redundant force optimization of other redundant parallel kinematic machines.     

Accurate dynamic modeling and control parameters design of an industrial hybrid spray-painting robot

To obtain higher performance for hybrid robots subject to nonlinear dynamics and friction, feedforward compensations have been ubiquitously utilized in the industrial robotic field to attenuate these disturbances. However, due to the complex friction model and the coupling and time-varying dynamic of hybrid robots, there is no effective approach to realize accurate feedforward compensations in industrial control systems. This paper investigated an accurate dynamic modeling and control parameters design method to address these issues all at once. Taking the friction of each joint into account, the accurate dynamic model of the hybrid robot is developed and verified by experiments. With the accurate dynamic model, an exact control parameter design method is proposed based on the mapping relationship between the dynamic model and the feedforward compensations. Additionally, the control system designed by the method proposed in this paper is compared with the one tuned by an experienced engineer. Particularly, the robot's position and motion accuracy are also tested by a third-party inspection agency. The experimental and test results show that the position and velocity accuracy of the robot is improved significantly when the control system is designed by using the method proposed in this paper, which proves the effectiveness of the proposed method.     

Quaternion-based Robust Trajectory Tracking Control of a Quadrotor Hover System

This paper presents a robust nonlinear output feedback control method that achieves three degree of freedom (3-DOF) attitude trajectory tracking of a hover system test bed. The proposed control method formally incorporates dynamic model uncertainty in addition to test bed voltage constraints. To reduce the computational requirement in the closed-loop system, constant feedforward estimates of the input-multiplicative parametric uncertainty are utilized in lieu of adaptive parameter estimates. To eliminate the need for angular rate measurements, the control design employs a bank of dynamic filters, which operates as a velocity estimator in the closed-loop system. A rigorous error system development and Lyapunov-based stability analysis are presented to prove asymptotic 3-DOF attitude trajectory tracking control. Computer simulation and experimental results are also included to illustrate the performance of the attitude control method using the Quanser 3-DOF hover system test bed.     

Neural network robust control of a 3-DOF hydraulic manipulator with asymptotic tracking

Multiaxial hydraulic manipulators are complicated systems with highly nonlinear dynamics and various modeling uncertainties, which hinders the development of high-performance controller. In this paper, a neural network feedforward with a robust integral of the sign of the error (RISE) feedback is proposed for high precise tracking control of hydraulic manipulator systems. The established nonlinear model takes three-axis dynamic coupling, hydraulic actuator dynamics, and nonlinear friction effects into consideration. A radial basis function neural network (RBFNN) is synthesized to approximate the uncertain system dynamics and external disturbance, which can greatly reduce the dependence on accurate system model. In addition, a continuous RISE feedback law is judiciously integrated to deal with the residual unknown dynamics. Since the major unknown dynamics can be estimated by the RBFNN and then compensated in the feedforward design, the high-gain feedback issue in RISE feedback control will be avoided. The proposed RISE-based neural network robust controller theoretically guarantees an excellent semi-global asymptotic stability. Comparative simulation is performed on a 3-DOF hydraulic manipulator, and the obtained results verify the effectiveness of the proposed controller.     

Adaptive Kalman filter and dynamic recurrent neural networks-based control design of macro-micro manipulator

In this paper,a composite control scheme for macro-micro dual-drive positioning stage with high acceleration and high precision is proposed.The objective of control is to improve the precision by reducing the influence of system vibration and external noise.The positioning stage is composed of voice coil motor(VCM) as macro driver and piezoelectric actuator(PEA) as micro driver.The precision of the macro drive positioning stage is improved by the combined PID control with adaptive Kalman filter(AKF).AKF is used to compensate VCM vibration(as the virtual noise) and the external noise.The control scheme of the micro drive positioning stage is presented as the integrated one with PID and intelligent adaptive inverse control approach to compensate the positioning error caused by macro drive positioning stage.A dynamic recurrent neural networks(DRNN) based inverse control approach is proposed to offset the hysteresis nonlinearity of PEA.Simulations show the positioning precision of macro-micro dual-drive stage is clearly improved via the proposed control scheme.